For example, I am currently doing a sensitivity analysis in checking how the volume of a spherical region-of-interest (ROI) influences comparisons of brain activity when comparing participants before and after a training intervention. There are 4 ROIs, and each have 3 different sizes. This is the table of p-values:

4mm 6mm 8mm

ROI1 0.020 0.059 0.029

ROI2 0.047 0.043 0.035

ROI3 0.047 0.197 0.011

ROI4 0.012 0.001 0.015

Obviously, the row-wise results are likely to show similarities given that the data is partially overlapping, while the p-values in each column are more independent. Bonferroni or FDR-correction does not really make sense to me in this situation.

Suggestions would be very welcome.